CN113671965A - Path planning method and device - Google Patents
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Abstract
The invention provides a path planning method and a device, comprising the following steps: acquiring the current position state of the robot group; when the distance between a first robot and other robots in the robot group except the first robot is smaller than a first threshold value, recording the position states of the two robots with the comparison result of being smaller than the first threshold value in a collision information list; based on the collision information list, a topological sorting method is applied to detect deadlock rings; and when the deadlock ring exists, applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path. The path planning method and the device can efficiently detect the collision and deadlock phenomena among the robots, and further more accurately plan the paths of the robots; in practical application, the method does not occupy resources of a physical machine and a virtual machine, and can run in software, so that the execution efficiency is improved; in addition, the application scene is wide, and various path planning requirements in thousands of code points under the simulation environment can be met.
Description
Technical Field
The invention relates to the field of intelligent warehousing traffic control and design, in particular to a path planning method and device.
Background
The intelligent warehousing construction is an important ring of modern logistics industry development, and the idea is to establish a more efficient, flexible and accurate warehousing system by utilizing automatic equipment and an intelligent management method so as to meet the requirement change of diversification and individuation of consumers. The intelligent warehouse is mainly used for sorting various commodities in a warehouse according to correct types and quantities of the commodities according to order contents issued by clients under the condition that a few workers assist and various automatic devices work cooperatively, then the commodities are respectively packed into cartons and sealed, and finally the commodities are sent to express receiving points of logistics companies to be loaded and transported out of the warehouse, wherein the most important automatic device working cooperatively is an Automatic Guided Vehicle (AGV) robot.
In the prior art, the route planning based on the robot and the related intelligent warehousing layout are directly generated based on the pre-sales planning, and because the simulation verification time is high in cost, effective reference for practical application cannot be formed, and the transportation efficiency under the practical intelligent warehousing mode is not high easily.
Therefore, how to efficiently plan the task path of the robot so as to quickly simulate and verify the task path is an urgent problem to be solved.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a path planning method and device, which is used to solve the problem in the prior art that the path of the robot executing the task cannot be efficiently planned so as to facilitate rapid simulation verification.
To achieve the above and other related objects, the present invention provides a method and apparatus for path planning, comprising the following steps: acquiring the current position state of the robot group; when the distance between a first robot and other robots in the robot group except the first robot is smaller than a first threshold value, recording the position states of the two robots with the comparison result of being smaller than the first threshold value in a collision information list; the first robot is any robot in the robot group; based on the collision information list, a topological sorting method is applied to detect deadlock rings; and when the deadlock ring exists, applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path.
In an embodiment of the present invention, the performing deadlock ring detection by using a topology sorting method based on the collision information list includes: based on the collision information list, creating a collision relation directed graph of the robot; determining a robot with an entrance degree of 0 based on the collision relation directed graph; traversing the collision relation directed graph based on the robot with the degree of entrance of 0, sequentially subtracting 1 from the degree of entrance of the robot associated with the robot with the degree of entrance of 0, and determining the updated collision relation directed graph; when the nodes of the robot exist in the collision relation directed graph, the nodes of the robot form the dead-lock ring.
In an embodiment of the present invention, the applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path when the deadlock ring exists includes: when the deadlock ring exists, marking the robot in the deadlock ring; moving the marked robot to a preset robot conflict resolution area; and re-planning the robot path by applying an A star algorithm based on the edge relation based on other robots of the robot group except the robot in the deadlock ring.
In an embodiment of the present invention, before the obtaining the current position status of the robot group, the method further includes: dividing the area where the robot is located at equal intervals according to X-axis and Y-axis coordinates in advance, and setting the passing direction of each divided grid node; based on the divided areas, the passing direction of each grid node and the tasks with preset starting positions and ending positions, determining the shortest path of each robot in the robot group for executing the corresponding task by applying an A star algorithm based on the edge relation; traversing each robot executing corresponding tasks according to the shortest path based on a preset time interval to acquire the current position state of the robot group; the position state includes an X-axis coordinate, a Y-axis coordinate, and the passing direction of each robot.
In an embodiment of the present invention, after the applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path when the deadlock ring exists, the method further includes: counting the number of tasks completed by each robot in the robot group within the preset time based on the preset time and the preset tasks; and evaluating the quality result of the robot path planning based on the number of the tasks.
Correspondingly, the invention provides a path planning device, comprising: the acquisition module is used for acquiring the current position state of the robot group; the determining module is used for recording the position states of two robots with the comparison result of being smaller than a first threshold value into a collision information list when the distance between a first robot and other robots in the robot group except the first robot is smaller than the first threshold value; the first robot is any robot in the robot group; the first processing module is used for detecting deadlock rings by applying a topological sorting method based on the collision information list; and the second processing module is used for applying a preset obstacle avoidance area planning method to remove the deadlock ring and replan the robot path when the deadlock ring exists.
In an embodiment of the present invention, the first processing module is specifically configured to: based on the collision information list, creating a collision relation directed graph of the robot; determining a robot with an entrance degree of 0 based on the collision relation directed graph; traversing the collision relation directed graph based on the robot with the degree of entrance of 0, sequentially subtracting 1 from the degree of entrance of the robot associated with the robot with the degree of entrance of 0, and determining the updated collision relation directed graph; when the nodes of the robot exist in the collision relation directed graph, the nodes of the robot form the dead-lock ring.
In an embodiment of the invention, the second processing module is specifically configured to: when the deadlock ring exists, marking the robot in the deadlock ring; moving the marked robot to a preset robot conflict resolution area; and re-planning the robot path by applying an A star algorithm based on the edge relation based on other robots of the robot group except the robot in the deadlock ring.
The invention provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the path planning method described above.
The invention provides a path planning platform, which comprises a memory, a route planning module and a route planning module, wherein the memory is used for storing a computer program; a processor for running the computer program to implement the path planning method described above.
As described above, the path planning method and apparatus of the present invention have the following advantages:
(1) the collision and deadlock phenomena among the robots can be efficiently detected, and the robot path can be planned more accurately.
(2) By the path planning method, a database does not need to be additionally imported, and the rapid simulation of the intelligent warehousing layout design can be realized only by depending on given task data in the simulation.
(3) In practical application, the method does not occupy resources of a physical machine and a virtual machine, can run in software, and improves execution efficiency.
(4) The method has wide application scenes and can meet various path planning requirements in thousands of code points under the simulation environment.
Drawings
Fig. 1 is a flowchart illustrating a path planning method according to an embodiment of the invention.
Fig. 2a is a schematic diagram illustrating an area where a robot is located in an embodiment of the path planning method of the present invention.
Fig. 2b is a schematic traffic direction diagram of the path planning method according to an embodiment of the invention.
Fig. 3 is a schematic diagram illustrating deadlock in an embodiment of a path planning method according to the present invention.
Fig. 4a is a layout comparison diagram of an S-shaped workstation inbound route map according to an embodiment of the route planning method of the present invention.
Fig. 4b is a layout diagram of back-to-back workstations according to the layout comparison method of the present invention.
Fig. 5 is a schematic structural diagram of a path planning apparatus according to an embodiment of the invention.
Fig. 6 shows a path planning platform of the path planning apparatus according to an embodiment of the invention.
Description of the element reference numerals
51 acquisition module
52 determination module
53 first processing module
54 second processing module
61 processor
62 memory
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
The path planning method and the device can efficiently detect the collision and deadlock phenomena among the robots, and further more accurately plan the paths of the robots; moreover, a database does not need to be additionally imported, the rapid simulation of the intelligent warehousing layout design can be realized only by depending on given task data in the simulation, physical machine and virtual machine resources are not occupied in the actual application, the intelligent warehousing layout design can be operated in software, and the execution efficiency is improved; in addition, the application scene is wide, and various path planning requirements in thousands of code points under the simulation environment can be met. As shown in fig. 1, in an embodiment, the path planning method of the present invention includes the following steps:
and step S1, acquiring the current position state of the robot group.
Specifically, the position state includes an X-axis coordinate, a Y-axis coordinate, and the passing direction of each robot.
Further specifically, before acquiring the current position state of the robot group, the method further includes:
dividing the area where the robot is located at equal intervals according to X-axis and Y-axis coordinates in advance, and setting the passing direction of each divided grid node; based on the divided areas, the passing direction of each grid node and the tasks with preset starting positions and ending positions, determining the shortest path of each robot in the robot group for executing the corresponding task by applying an A star algorithm based on the edge relation; traversing each robot executing corresponding tasks according to the shortest path based on a preset time interval, and acquiring the current position state of the robot group.
The processing of dividing the area where the robot is located at equal intervals according to X-axis and Y-axis coordinates in advance and setting the passing direction of each grid node after division comprises the following steps: the area where the robot is located corresponds to a corresponding map element file in advance, and the map element file represents corresponding map elements according to numbers, for example, 0 represents a forbidden point, 1 represents a path point and the like; the passing direction of each mesh node includes any one of the four directions, i.e., up, down, left, and right, and the passing direction of the current mesh node is set according to the map element file, as shown in fig. 2a, the schematic diagram of the area where the robot is located in the embodiment and the schematic diagram of the passing direction in the embodiment as shown in fig. 2 b.
Then, based on the divided areas, the passing direction of each grid node and the tasks with preset starting positions and ending positions, the processing for determining the shortest path for each robot in the robot group to execute the corresponding task by applying an edge relation-based A star algorithm comprises the following steps: different tasks are set for different robots in advance, each robot is set with a plurality of tasks, and meanwhile, the cost of the robot when passing in the grid nodes in the upper direction, the lower direction, the left direction and the right direction is set; and then, determining the shortest path of each robot in the robot group for executing the corresponding task by applying an A star algorithm based on the edge relation. Among them, the determination of the shortest path is divided into the following 2 cases.
In the first case, when the robot is at a starting position, for example, the starting position is a task shelf, then the distance from the starting position to an ending position is directly calculated, for example, the ending position is a task workstation, when the distance is calculated, an a-star algorithm based on an edge relationship is applied, cost when the robot passes in 4 directions of grid nodes is considered, and the shortest path with the shortest path length is selected from calculated path lengths containing the cost of the 4 passing directions as the shortest path for the robot to execute the task.
In case two, when the deadlock ring is released and the robot path is re-planned in the subsequent step S4, the robot is in the process of executing the current task, that is, the current position is not the starting position, and at this time, when the distance to the ending position is calculated, on the basis of the calculation of case one, the calculation of the distance from the current position to the starting position needs to be considered, and finally, the shortest path is comprehensively calculated and selected.
After the shortest path of the robot for executing a certain task is obtained according to the method, the grid node where each step is located and the passing direction of the next step when the robot executes the task can be obtained, and in the executing process, if the next grid node has other robots or is a workstation and a reversing point, the robot waits for the preset time and then moves to the grid node; if the situation does not occur, the path point is a normal path point, waiting is not needed, and the next step is directly executed and the network node is moved to.
Step S2, when the distance between the first robot and the other robots in the robot group except the first robot is smaller than a first threshold value, recording the position states of the two robots with the comparison result smaller than the first threshold value in a collision information list; the first robot is any robot in the robot group.
Specifically, after the current position state of the robot group is obtained, according to the X-axis coordinate and the Y-axis coordinate of the robot in the position state, corresponding to 4 passing directions, it is determined whether the distance between the first robot and the other robots except the first robot is smaller than a first threshold, and when the comparison result is smaller than the first threshold, the position states of the two robots are recorded in a collision information list, where the collision information list includes: robot number, passing direction of the robot, and number of the collided robot.
And step S3, based on the collision information list, applying a topological sorting method to detect the deadlock ring.
Specifically, based on the collision information list, a collision relation directed graph of the robot is created; determining a robot with an entrance degree of 0 based on the collision relation directed graph; traversing the collision relation directed graph based on the robot with the degree of entrance of 0, sequentially subtracting 1 from the degree of entrance of the robot associated with the robot with the degree of entrance of 0, and determining the updated collision relation directed graph; when the nodes of the robot exist in the collision relation directed graph, the nodes of the robot form the dead-lock ring.
The nodes in the collision relation directed graph are robots in the collision information list, and the direction of the directed edges in the collision relation directed graph is set to be that when the robot A collides with the robot B when the robot A executes the next step according to the traffic direction, the robot A points to the robot B; after the creation is completed, selecting a robot number with an introductivity of 0 in a collision relation directed graph, pressing the selected robot number into a stack list in a stacking manner, popping up one robot number with an introductivity of 0 from a stack each time, namely traversing the collision relation directed graph, deleting directed edges of other robots related to the robot with the introductivity of 0 until all the robot numbers with the introductivity of 0 are popped up from the stack, updating the collision relation directed graph, and when nodes of the robots still exist in the collision relation directed graph, forming a deadlock ring by the nodes of the robots, as shown in fig. 3, a deadlock schematic diagram in this embodiment.
And step S4, when the deadlock ring exists, applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path.
Specifically, when the deadlock ring exists, marking the robot in the deadlock ring; moving the marked robot to a preset robot conflict resolution area; based on other robots of the robot group except the robot in the deadlock ring, an A star algorithm based on an edge relation is applied to re-plan a robot path; the robot conflict resolution area can be arranged beside the task workstation and is used for isolating and avoiding influencing the normal task execution of other robots; after all the robots in the deadlock ring are introduced to the area, the other robots in the robot group re-plan the shortest paths of the robots according to the shortest path calculation method in case two in step S1.
Further specifically, after the deadlock ring is removed and the robot path is re-planned, the collision information list is emptied, and after a preset time interval, the robots executing corresponding tasks according to the shortest path are traversed again to obtain the current position state of the robot group, and the collision information judgment and detection, the deadlock ring unlocking and the path re-planning in the steps are performed.
Further specifically, after the deadlock ring is released and the robot path is re-planned, the method further comprises: counting the number of tasks completed by each robot in the robot group within the preset time based on the preset time and the preset tasks; and evaluating the quality result of the robot path planning based on the number of the tasks. For example, the statistical time of the relevant timer is set to 1 hour, when the statistical time is up, the current number of tasks completed by each robot is returned and counted, and the quality result of the robot path plan is judged according to the total number of tasks completed by each robot within 1 hour, so that a better intelligent warehousing layout can be tested, as shown in fig. 4a, the layout in the embodiment is compared with the station-entering route diagram of the S-shaped workstation in the diagram; as shown in fig. 4b, the layout of the back-to-back workstation design in this embodiment is compared with the number of tasks performed by different robots in the two layouts as shown in table one below.
Watch 1
From the steps S1 to S4, the path planning method and apparatus of the present invention can efficiently detect the collision and deadlock between robots, and further more accurately plan the robot path; moreover, a database does not need to be additionally imported, the rapid simulation of the intelligent warehousing layout design can be realized only by depending on given task data in the simulation, physical machine and virtual machine resources are not occupied in the actual application, the intelligent warehousing layout design can be operated in software, and the execution efficiency is improved; in addition, the application scene is wide, and various path planning requirements in thousands of code points under the simulation environment can be met.
As shown in fig. 5, in an embodiment, the path planning apparatus of the present invention includes:
an obtaining module 51, configured to obtain a current position state of the robot group;
a determining module 52, configured to record, when the distance between a first robot and another robot in the robot group except the first robot is smaller than a first threshold, the position statuses of the two robots whose comparison results are smaller than the first threshold in a collision information list; the first robot is any robot in the robot group;
the first processing module 53 is configured to perform deadlock ring detection by applying a topology ranking method based on the collision information list;
and the second processing module 54 is configured to, when the deadlock ring exists, apply a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path.
The first processing module 53 is specifically configured to:
based on the collision information list, creating a collision relation directed graph of the robot;
determining a robot with an entrance degree of 0 based on the collision relation directed graph;
traversing the collision relation directed graph based on the robot with the degree of entrance of 0, sequentially subtracting 1 from the degree of entrance of the robot associated with the robot with the degree of entrance of 0, and determining the updated collision relation directed graph;
when the nodes of the robot exist in the collision relation directed graph, the nodes of the robot form the dead-lock ring.
The second processing module 54 is specifically configured to:
when the deadlock ring exists, marking the robot in the deadlock ring;
moving the marked robot to a preset robot conflict resolution area;
and re-planning the robot path by applying an A star algorithm based on the edge relation based on other robots of the robot group except the robot in the deadlock ring.
The technical features of the specific implementation of the path planning apparatus in this embodiment are basically the same as the principles of the steps in the path planning method in embodiment 1, and the general technical contents between the method and the apparatus are not repeated.
The storage medium of the present invention stores thereon a computer program which, when executed by a processor, implements the path planning method described above.
As shown in fig. 6, in an embodiment, the path planning platform of the present invention includes: a processor 61 and a memory 62.
The memory 62 is used for storing computer programs.
The memory 62 includes: various media that can store program codes, such as ROM, RAM, magnetic disk, U-disk, memory card, or optical disk.
The processor 61 is connected to the memory 62, and is configured to execute the computer program stored in the memory 62, so that the path planning platform executes the path planning method described above.
Preferably, the Processor 61 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In conclusion, the path planning method and the path planning device can efficiently detect the collision and deadlock phenomena among the robots, and further more accurately plan the paths of the robots; moreover, a database does not need to be additionally imported, the rapid simulation of the intelligent warehousing layout design can be realized only by depending on given task data in the simulation, physical machine and virtual machine resources are not occupied in the actual application, the intelligent warehousing layout design can be operated in software, and the execution efficiency is improved; in addition, the application scene is wide, and various path planning requirements in thousands of code points under the simulation environment can be met. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A path planning method, characterized in that the path planning method comprises the steps of:
acquiring the current position state of the robot group;
when the distance between a first robot and other robots in the robot group except the first robot is smaller than a first threshold value, recording the position states of the two robots with the comparison result of being smaller than the first threshold value in a collision information list; the first robot is any robot in the robot group;
based on the collision information list, a topological sorting method is applied to detect deadlock rings;
and when the deadlock ring exists, applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path.
2. The method of claim 1, wherein the applying a topological ordering method for deadlock ring detection based on the list of collision information comprises:
based on the collision information list, creating a collision relation directed graph of the robot;
determining a robot with an entrance degree of 0 based on the collision relation directed graph;
traversing the collision relation directed graph based on the robot with the degree of entrance of 0, sequentially subtracting 1 from the degree of entrance of the robot associated with the robot with the degree of entrance of 0, and determining the updated collision relation directed graph;
when the nodes of the robot exist in the collision relation directed graph, the nodes of the robot form the dead-lock ring.
3. The method of claim 2, wherein the applying a preset obstacle avoidance area planning method to remove the deadlock ring and re-plan the robot path when the deadlock ring exists comprises:
when the deadlock ring exists, marking the robot in the deadlock ring;
moving the marked robot to a preset robot conflict resolution area;
and re-planning the robot path by applying an A star algorithm based on the edge relation based on other robots of the robot group except the robot in the deadlock ring.
4. The method of claim 1, wherein prior to obtaining the current position status of the robotic assembly, further comprising:
dividing the area where the robot is located at equal intervals according to X-axis and Y-axis coordinates in advance, and setting the passing direction of each divided grid node;
based on the divided areas, the passing direction of each grid node and the tasks with preset starting positions and ending positions, determining the shortest path of each robot in the robot group for executing the corresponding task by applying an A star algorithm based on the edge relation;
traversing each robot executing corresponding tasks according to the shortest path based on a preset time interval to acquire the current position state of the robot group; the position state includes an X-axis coordinate, a Y-axis coordinate, and the passing direction of each robot.
5. The method according to claim 1, wherein after applying a preset obstacle avoidance area planning method to release the deadlock ring and re-plan the robot path when the deadlock ring exists, the method further comprises:
counting the number of tasks completed by each robot in the robot group within the preset time based on the preset time and the preset tasks; and evaluating the quality result of the robot path planning based on the number of the tasks.
6. A path planning apparatus, comprising:
the acquisition module is used for acquiring the current position state of the robot group;
the determining module is used for recording the position states of two robots with the comparison result of being smaller than a first threshold value into a collision information list when the distance between a first robot and other robots in the robot group except the first robot is smaller than the first threshold value; the first robot is any robot in the robot group;
the first processing module is used for detecting deadlock rings by applying a topological sorting method based on the collision information list;
and the second processing module is used for applying a preset obstacle avoidance area planning method to remove the deadlock ring and replan the robot path when the deadlock ring exists.
7. The apparatus of claim 6, wherein the first processing module is specifically configured to:
based on the collision information list, creating a collision relation directed graph of the robot;
determining a robot with an entrance degree of 0 based on the collision relation directed graph;
traversing the collision relation directed graph based on the robot with the degree of entrance of 0, sequentially subtracting 1 from the degree of entrance of the robot associated with the robot with the degree of entrance of 0, and determining the updated collision relation directed graph;
when the nodes of the robot exist in the collision relation directed graph, the nodes of the robot form the dead-lock ring.
8. The apparatus according to claim 7, wherein the second processing module is specifically configured to:
when the deadlock ring exists, marking the robot in the deadlock ring;
moving the marked robot to a preset robot conflict resolution area;
and re-planning the robot path by applying an A star algorithm based on the edge relation based on other robots of the robot group except the robot in the deadlock ring.
9. A storage medium storing program instructions, wherein the program instructions, when executed, implement the steps of the path planning method according to any one of claims 1 to 5.
10. A path planning platform, characterized by: comprising a memory for storing a computer program; a processor for running the computer program to implement the steps of the path planning method according to any one of claims 1 to 5.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114674322A (en) * | 2022-03-30 | 2022-06-28 | 同济大学 | Heuristic path planning method, device and medium under single-channel scene |
| CN114815857A (en) * | 2022-06-28 | 2022-07-29 | 广东邦盛北斗科技股份公司 | Intelligent agricultural machinery management method and system based on Beidou navigation and cloud platform |
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